from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 14.0 | 47.404542 |
| daal4py_KNeighborsClassifier | 0.0 | 5.0 | 46.588274 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 25.657507 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 55.493755 |
| KMeans_tall | 0.0 | 1.0 | 47.564210 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 19.469896 |
| KMeans_short | 0.0 | 0.0 | 29.087693 |
| daal4py_KMeans_short | 0.0 | 0.0 | 15.081865 |
| LogisticRegression | 0.0 | 1.0 | 18.642543 |
| daal4py_LogisticRegression | 0.0 | 1.0 | 11.708509 |
| Ridge | 0.0 | 1.0 | 11.542230 |
| daal4py_Ridge | 0.0 | 0.0 | 28.741659 |
| total | 0.0 | 36.0 | 57.081772 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.158 | 0.006 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.575 | 0.007 | 0.275 | 0.001 | See |
| 1 | KNeighborsClassifier | predict | 0.207 | 0.018 | 1000000 | 1 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 0.111 | 0.004 | 1.874 | 0.009 | See |
| 2 | KNeighborsClassifier | predict | 34.988 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 4.549 | 0.051 | 7.691 | 0.000 | See |
| 3 | KNeighborsClassifier | fit | 0.154 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.583 | 0.014 | 0.263 | 0.001 | See |
| 4 | KNeighborsClassifier | predict | 0.201 | 0.014 | 1000000 | 1 | 100 | brute | -1 | 5 | 1.0 | 0.0 | 0.108 | 0.003 | 1.865 | 0.005 | See |
| 5 | KNeighborsClassifier | predict | 42.143 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 1.0 | 0.0 | 4.571 | 0.037 | 9.219 | 0.000 | See |
| 6 | KNeighborsClassifier | fit | 0.153 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.568 | 0.017 | 0.269 | 0.001 | See |
| 7 | KNeighborsClassifier | predict | 0.204 | 0.018 | 1000000 | 1 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 0.111 | 0.007 | 1.836 | 0.011 | See |
| 8 | KNeighborsClassifier | predict | 42.157 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 4.638 | 0.030 | 9.089 | 0.000 | See |
| 9 | KNeighborsClassifier | fit | 0.152 | 0.004 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.599 | 0.020 | 0.254 | 0.002 | See |
| 10 | KNeighborsClassifier | predict | 0.224 | 0.003 | 1000000 | 1 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 0.107 | 0.001 | 2.089 | 0.000 | See |
| 11 | KNeighborsClassifier | predict | 18.028 | 0.051 | 1000000 | 1000 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 4.596 | 0.047 | 3.923 | 0.000 | See |
| 12 | KNeighborsClassifier | fit | 0.154 | 0.006 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.589 | 0.012 | 0.261 | 0.002 | See |
| 13 | KNeighborsClassifier | predict | 0.233 | 0.005 | 1000000 | 1 | 100 | brute | 1 | 5 | 1.0 | 0.0 | 0.114 | 0.002 | 2.047 | 0.001 | See |
| 14 | KNeighborsClassifier | predict | 26.298 | 0.036 | 1000000 | 1000 | 100 | brute | 1 | 5 | 1.0 | 0.0 | 4.665 | 0.109 | 5.638 | 0.001 | See |
| 15 | KNeighborsClassifier | fit | 0.152 | 0.005 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.591 | 0.009 | 0.257 | 0.002 | See |
| 16 | KNeighborsClassifier | predict | 0.234 | 0.007 | 1000000 | 1 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 0.110 | 0.003 | 2.139 | 0.002 | See |
| 17 | KNeighborsClassifier | predict | 26.876 | 0.238 | 1000000 | 1000 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 4.677 | 0.036 | 5.747 | 0.000 | See |
| 18 | KNeighborsClassifier | fit | 0.055 | 0.002 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.101 | 0.003 | 0.547 | 0.002 | See |
| 19 | KNeighborsClassifier | predict | 0.021 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.005 | 0.000 | 4.485 | 0.025 | See |
| 20 | KNeighborsClassifier | predict | 25.910 | 0.329 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 1.002 | 0.010 | 25.868 | 0.000 | See |
| 21 | KNeighborsClassifier | fit | 0.053 | 0.003 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.101 | 0.004 | 0.524 | 0.004 | See |
| 22 | KNeighborsClassifier | predict | 0.028 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.005 | 0.001 | 5.958 | 0.025 | See |
| 23 | KNeighborsClassifier | predict | 33.909 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 1.018 | 0.014 | 33.324 | 0.000 | See |
| 24 | KNeighborsClassifier | fit | 0.055 | 0.004 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.102 | 0.005 | 0.538 | 0.008 | See |
| 25 | KNeighborsClassifier | predict | 0.026 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.006 | 0.001 | 4.371 | 0.031 | See |
| 26 | KNeighborsClassifier | predict | 33.089 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 1.089 | 0.012 | 30.388 | 0.000 | See |
| 27 | KNeighborsClassifier | fit | 0.054 | 0.002 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.105 | 0.005 | 0.509 | 0.003 | See |
| 28 | KNeighborsClassifier | predict | 0.013 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.005 | 0.001 | 2.601 | 0.029 | See |
| 29 | KNeighborsClassifier | predict | 11.825 | 0.108 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 1.021 | 0.014 | 11.580 | 0.000 | See |
| 30 | KNeighborsClassifier | fit | 0.069 | 0.002 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.108 | 0.003 | 0.639 | 0.002 | See |
| 31 | KNeighborsClassifier | predict | 0.020 | 0.002 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.005 | 0.001 | 3.843 | 0.019 | See |
| 32 | KNeighborsClassifier | predict | 21.789 | 0.301 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 1.018 | 0.012 | 21.397 | 0.000 | See |
| 33 | KNeighborsClassifier | fit | 0.073 | 0.005 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.100 | 0.008 | 0.729 | 0.010 | See |
| 34 | KNeighborsClassifier | predict | 0.021 | 0.002 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.005 | 0.000 | 4.268 | 0.013 | See |
| 35 | KNeighborsClassifier | predict | 20.646 | 0.019 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 1.096 | 0.022 | 18.841 | 0.000 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 2.853 | 0.116 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.790 | 0.019 | 3.613 | 0.002 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 5.005 | 0.393 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.441 | 0.008 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.120 | 0.001 | 3.680 | 0.000 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 2.858 | 0.164 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 0.814 | 0.012 | 3.512 | 0.003 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 4.181 | 0.161 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.923 | 0.020 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.220 | 0.006 | 4.195 | 0.001 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 2.774 | 0.106 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.771 | 0.013 | 3.596 | 0.002 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.005 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.002 | 0.001 | 2.699 | 0.166 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 3.005 | 0.036 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.669 | 0.009 | 4.490 | 0.000 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 2.679 | 0.037 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.820 | 0.012 | 3.265 | 0.000 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 1.950 | 0.370 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.756 | 0.015 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.122 | 0.002 | 6.200 | 0.001 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 2.729 | 0.092 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.784 | 0.009 | 3.483 | 0.001 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 2.022 | 0.599 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.446 | 0.037 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.234 | 0.007 | 6.188 | 0.002 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 2.606 | 0.067 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 0.864 | 0.052 | 3.016 | 0.004 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.002 | 0.001 | 1.902 | 0.286 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 4.833 | 0.131 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.706 | 0.024 | 6.848 | 0.002 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.264 | 0.027 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.566 | 0.016 | 2.231 | 0.001 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 10.798 | 1.262 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.038 | 0.002 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 38.293 | 0.170 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.262 | 0.032 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.577 | 0.021 | 2.186 | 0.002 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 10.894 | 0.467 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.036 | 0.002 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.002 | 0.001 | 20.607 | 0.462 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.262 | 0.061 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.578 | 0.019 | 2.184 | 0.003 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 10.625 | 0.261 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.054 | 0.003 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.008 | 0.001 | 6.785 | 0.011 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.231 | 0.030 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.588 | 0.061 | 2.094 | 0.012 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.001 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 5.690 | 0.805 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.034 | 0.003 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 34.042 | 0.073 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.272 | 0.024 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.547 | 0.013 | 2.324 | 0.001 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 3.806 | 0.309 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.041 | 0.003 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.002 | 0.001 | 26.883 | 0.121 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.291 | 0.044 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.552 | 0.009 | 2.337 | 0.001 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 4.451 | 0.117 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.072 | 0.004 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.008 | 0.001 | 8.735 | 0.010 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.696 | 0.011 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.359 | 0.009 | 1.940 | 0.001 | See |
| 1 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.122 | 0.360 | See |
| 2 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.834 | 0.294 | See |
| 3 | KMeans_tall | fit | 0.607 | 0.024 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.312 | 0.012 | 1.945 | 0.003 | See |
| 4 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.989 | 0.463 | See |
| 5 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.840 | 0.449 | See |
| 6 | KMeans_tall | fit | 8.818 | 0.105 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 4.517 | 0.064 | 1.952 | 0.000 | See |
| 7 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.939 | 0.512 | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.935 | 0.240 | See |
| 9 | KMeans_tall | fit | 7.884 | 0.083 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 4.308 | 0.058 | 1.830 | 0.000 | See |
| 10 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.022 | 0.604 | See |
| 11 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.221 | 0.197 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.448 | 0.023 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.181 | 0.008 | 2.481 | 0.004 | See |
| 1 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.091 | 0.275 | See |
| 2 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.244 | 0.117 | See |
| 3 | KMeans_short | fit | 0.160 | 0.006 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.082 | 0.002 | 1.940 | 0.002 | See |
| 4 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.833 | 0.291 | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.117 | 0.047 | See |
| 6 | KMeans_short | fit | 1.406 | 0.052 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 19.0 | NaN | 17.0 | NaN | 0.694 | 0.040 | 2.025 | 0.005 | See |
| 7 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.180 | 0.420 | See |
| 8 | KMeans_short | predict | 0.008 | 0.002 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.002 | 0.000 | 4.610 | 0.136 | See |
| 9 | KMeans_short | fit | 0.408 | 0.056 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 19.0 | NaN | 24.0 | NaN | 0.373 | 0.050 | 1.094 | 0.037 | See |
| 10 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.824 | 0.327 | See |
| 11 | KMeans_short | predict | 0.010 | 0.001 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.002 | 0.000 | 6.064 | 0.036 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 17.587 | 0.033 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 17.584 | 0.127 | 1.000 | 0.000 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.392 | 0.784 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.001 | 0.000 | 0.953 | 0.281 | See |
| 3 | LogisticRegression | fit | 1.447 | 0.042 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 1.525 | 0.035 | 0.949 | 0.001 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.001 | 0.000 | 0.161 | 0.237 | See |
| 5 | LogisticRegression | predict | 0.003 | 0.001 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.004 | 0.000 | 0.818 | 0.083 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 3.246 | 0.070 | 100000 | 100000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 1.927 | 0.026 | 1.684 | 0.001 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 100000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 1.581 | 2.908 | See |
| 2 | Ridge | predict | 0.001 | 0.000 | 100000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.001 | 0.000 | 0.749 | 0.129 | See |
| 3 | Ridge | fit | 1.714 | 0.043 | 1000000 | 1000000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.430 | 0.007 | 3.991 | 0.001 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.492 | 0.529 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.701 | 0.306 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
"system_info": {
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"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
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"scipy": "1.6.2",
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"joblib": "1.0.1",
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